"OpenAI Gym" matching MCP servers:

An MCP server that provides long-term memory and semantic search using Qdrant and OpenAI embeddings, with tools for storing, searching, and managing knowledge.

Enables semantic search, code exemplar lookup, knowledge-graph statistics, and cached retrieval over locally ingested notebook and Markdown content through MCP.

Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.

A research assistant server that enables saving, organizing, and retrieving research content with semantic search using ChromaDB and OpenAI embeddings.

A shared memory layer for AI agents — one memory.md synced across Claude Desktop, Cursor, Claude Code, OpenAI Codex, and any MCP client.

Enables AI assistants to save and search bookmarks with semantic search using OpenAI, allowing storage of URLs with metadata and intelligent retrieval across collections.

OpenKai is an open-source MCP server that gives AI agents persistent memory across conversations, supporting core, long-term, short-term, episodic, and working memory types with goals, emotional intelligence, and temporal queries.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

Enables AI assistants to save, retrieve, and manage research content using ChromaDB vector storage with semantic search, topic organization, and automatic deduplication powered by OpenAI embeddings.

Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.

A Model Context Protocol server that enables intelligent document search and retrieval from PDF collections, providing semantic search capabilities powered by OpenAI embeddings and ChromaDB vector storage.

Enables lossless context management for OpenAI Codex CLI by capturing and compressing conversation history in SQLite, with lexical recall via MCP tools.

Enables voice captures from a smart ring to search and append notes in a local Obsidian vault and query an OpenAI-compatible AI agent, returning answers as phone notifications.

Enables real-time communication and shared vector memory between Claude Code, OpenAI Codex CLI, and Google Gemini CLI. It allows different AI platforms to exchange messages, share context, and collaborate through a unified MCP interface.

Enables persistent, project-scoped memory for OpenAI Codex Desktop and CLI on Windows, capturing prompts and responses through managed hooks, with federated recall across projects and optional local graph extraction.

A local knowledge base server that connects to AI assistants, turning markdown files into a semantically searchable memory layer via OpenAI embeddings and SQLite.

Enables searching local OpenAI Codex conversation history by keywords, project, date, or role, listing sessions, and retrieving exact supporting messages through MCP tools.

A fully local AI stack that provides OpenAI/Anthropic-compatible LLM API, embeddings, mem0 memory, and second-brain RAG via MCP tools, all running independently with no cloud dependencies.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

A local Mem0 MCP server for macOS with a menu bar toggle, storing memories locally in Chroma and using any OpenAI-compatible LLM for fact extraction.